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All Journal Jurnal Simantec Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization JIKO (Jurnal Informatika dan Komputer) JURNAL PengaMAS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Sistem Cerdas Building of Informatics, Technology and Science Jurnal Abdimas Mandiri Jurnal Ilmiah Ilmu dan Teknologi Rekayasa Jurnal Pengabdian UNDIKMA Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ International Journal of Global Operations Research Green Intelligent Systems and Applications JURNAL POLI-TEKNOLOGI J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Journal of Computer Engineering, Electronics and Information Technology Power Elektronik : Jurnal Orang Elektro In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Deden Pradeka
Universitas Pendidikan Indonesia
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Pelatihan Peningkatan Kemampuan Computational Thingking Guru dengan Media Robotik di SMP Santa Ursula Bandung Munawir; Dwi Putra, Muhammad Taufik; Pradeka, Deden; Adiwilaga, Anugrah; Pararta, Muhammad Salam
Jurnal Abdimas Mandiri Vol. 8 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v8i3.4704

Abstract

Tujuan dari dilaksanakannya pengabdian ini adalah untuk meningkatkan kemampuan berpikir komputasional guru di SMP Santa Ursula Bandung. Metode-metode yang diterapkan dalam pengabdian ini meliputi ceramah, praktik langsung, dan diskusi interaktif. Sebanyak 25 guru diikutsertakan dalam pelatihan ini, dan evaluasi kegiatan dilakukan menggunakan instrumen yang disediakan melalui Google Form yang kemudian dianalisis secara deskriptif. Hasil dari pengabdian ini menunjukkan adanya peningkatan capaian hasil belajar siswa yang diajarkan dengan penerapan ilmu teknologi robotika. Dengan analisis uji normalitas menggunakan N-Gain, didapatkan peningkatan pada nilai-nilai yang berkaitan dengan kompetensi siswa dalam pembelajaran. Para siswa cenderung lebih aktif dan mudah memahami konsep-konsep pelajaran ketika diberikan pemeragaan menggunakan robot. Hal ini ditunjukkan dengan rata-rata nilai efektivitas N-Gain di angka 40%. Dengan dilaksanakannya pelatihan ini, diharapkan para guru dapat menerapkan ilmu teknologi robotika sebagai media pembelajaran dalam kegiatan belajar mengajar di kelas. Penerapan teknologi ini tidak hanya membantu siswa memahami materi pelajaran dengan lebih baik, tetapi juga mempersiapkan mereka untuk menghadapi tantangan di era digital. Pelatihan ini juga diharapkan dapat meningkatkan kompetensi guru dalam mengintegrasikan teknologi dalam proses pembelajaran, sehingga menciptakan lingkungan belajar yang lebih interaktif dan inovatif. Dengan demikian, tujuan utama dari pengabdian ini dapat tercapai, yaitu meningkatkan kualitas pendidikan melalui pemanfaatan teknologi yang tepat guna.
Optimization of Traffic Light Control Using Fuzzy Logic Sugeno Method Kartikasari, Ria Yuliani; Prakarsa, Graha; Pradeka, Deden
International Journal of Global Operations Research Vol. 1 No. 2 (2020): International Journal of Global Operations Research (IJGOR), May 2020
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v1i2.37

Abstract

Congestion is one of the big problems around the world, especially for big cities. Intersections are the scene of congestion because the lane is the meeting point of two or more roads which has a major influence on the smooth flow of vehicles on the road network. This congestion occurs due to various factors, one of which is the statistical traffic light duration, which does not match traffic conditions. Based on this, there needs to be a development in the timing of a more adaptive green light. This study describes the design of a traffic light controller using the Sugeno method fuzzy logic. This study aims to design a green light duration calculation by applying fuzzy logic that results in adaptive traffic light duration at intersections, by entering the density of each intersection path, which is divided into 4 inputs, namely regulated lane density, opposing lane density I, and opposite lane density. II, the density of the opposite lane III, with the aim of the system being able to produce a duration that is in accordance with the current traffic situation with an output in the form of a green light duration on the regulated lane.
Spam and Phishing Whatsapp Message Filtering Application Using TF - IDF and Machine Learning Methods Manurung, Ferdinand Aprillian; Munawir; Pradeka, Deden
Green Intelligent Systems and Applications Volume 5 - Issue 1 - 2025
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v5i1.551

Abstract

The rapid development of communication technology has led to an increase in the number of unwanted messages, such as spam and phishing attempts. However, this progress has not been accompanied by sufficient user awareness of the basics of technology use. Additionally, the enforcement of laws regarding internet-based crimes remains unclear, further increasing the risk for users of internet technology to fall victim to such crimes. As one of the media prone to spam and phishing, WhatsApp is the focus of this research, which aims to develop an application capable of filtering spam and phishing messages. The application employs the TF-IDF (Term Frequency-Inverse Document Frequency) method and machine learning using the Random Forest model. It is developed using the MVVM (Model-View-ViewModel) architecture, enabling the separation of business logic from the user interface, thereby improving development and maintenance efficiency. The research findings demonstrate that the combination of TF-IDF and Random Forest achieves high accuracy in classifying spam and phishing messages. Performance evaluation using a confusion matrix reveals an accuracy rate of 92%. For the safe message class, the precision, recall, and F1 scores are 89%, 95%, and 92%, respectively, while for the dangerous message class, the scores are 95%, 88%, and 92%, respectively. Furthermore, the integration of the model and application performed exceptionally well, as evidenced by black-box testing results. All test scenarios were met, successfully detecting test messages with 98% accuracy. Therefore, the developed application provides enhanced protection for WhatsApp users against digital threats.
Designing A Pdf Malware Detection System Using Machine Learning Salman Abdul Jabbaar Wiharja; Deden Pradeka; Wirmanto Suteddy
Jurnal Poli-Teknologi Vol. 23 No. 1 (2024)
Publisher : Politeknik Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/pt.v23i1.6540

Abstract

This research proposes an approach to build malicious PDF detection system using random forest algorithm, focusing the Evasive-PDFMal2022 dataset which is updated and extended with the addition of new datasets. This dataset includes malicious PDF files from CVE and Exploit-DB, non-malicious PDF files, as well as files from private collections and Technically-oriented PDF Collection. Features were extracted using the PDFID tool, resulting in 29 structural features that formed the basis for the Random Forest classification algorithm. Experiments showed that the model trained with the new dataset provided accuracy equivalent to the Evasive-PDFMal2022 model, at 98%, albeit with a small decrease in recall for the benign class. In addition, this research involved the creation of a website for metadata extraction and malicious PDF detection. Recognition goes to the dataset contributors, tool developers, and dataset providers from NIST and Exploit-DB. Overall, this research successfully increased the representation and diversity of the dataset, provided good model training results, improved detection from 3 malicious PDF variants to 13 variants, and created a practical tool for malicious PDF extraction and detection. Nonetheless, further development may be required to improve detection performance in more complex scenarios
Batiknet: Batik Classification-based Management Application for Inexperienced User Putra, Muhammad Taufik Dwi; Pradana, Hilmil; Munawir, Munawir; Pradeka, Deden; Yuniarti, Ana Rahma; Sadik, Jafar; Andhika R, Muhammad
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.3086

Abstract

Batik has significantly contributed to the Indonesian economy, is diverse, and is spread throughout cities. Currently, batik patterns are very diverse and spread from Sabang to Merauke. Each batik pattern holds distinct meanings, philosophies of life, and ancestral heritage and reflects the region where it was crafted. We introduce a new batik dataset containing five patterns: Kawung, Megamendung, Parang, Sekarjagad, and Truntum. The Convolutional Neural Network (CNN) method is an effective Deep Learning method for extracting image information. CNNs have become the state of the art for various image processing tasks, such as classification, segmentation, and object recognition. This study used several state-of-the-art architectures, including Xception, ResNet50V2, MobileNetV2, and DenseNet169. However, we chose EfficientNetV2 as the primary feature extractor due to its superior performance. Our results show that EfficientNetV2 outperformed other architectures in training, validation, and testing accuracy, making it the best choice for classifying batik patterns. The training process resulted in an accuracy of 98% for training, 97% for validation, and 96% for testing. To ensure the accessibility and practical application of this research, we developed a user-friendly, web-based interface with a RESTful API, making the tool accessible to a broader audience. The application is named "BatikNet," a name chosen to reflect the blend of traditional batik culture ("Batik") with neural network technology ("Net"). This research contributes a valuable dataset and a practical tool for future studies and applications in batik pattern recognition and supports the preservation and understanding of Indonesian cultural heritage
Pengembangan Aplikasi Android PiGANO untuk Keamanan Pesan Menggunakan Kombinasi Caesar Cipher dan LSB Saragi, Muhammad Salam Pararta; Khoir, Farhan Ramadhan; Auriel, Muhammad; Fauziah, Rahmah; Maulana, Rajih Nibras; Humaira, Syifa Aqila; Pradeka, Deden; Khaerunnisa, Zahra
Power Elektronik : Jurnal Orang Elektro Vol 14, No 1 (2025): POWER ELEKTRONIK
Publisher : Politeknik Harapan Bersama Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/polektro.v14i1.8199

Abstract

Keamanan data menjadi hal yang sangat penting untuk melindungi kerahasiaan dari seseorang. Keamanan dan kerahasiaan data berpengaruh terhadap proses pertukaran pesan penting. Banyak teknik keamanan data yang dapat digunakan demi menjaga kerahasiaan pesan dari pihak lain, meliputi kriptografi dan steganografi. Penelitian ini bertujuan mengembangkan aplikasi Android bernama PiGANO yang menggabungkan algoritma Caesar Cipher dan Least significant bit (LSB) guna meningkatkan keamanan dan kerahasiaan pesan dalam media gambar. Proses penelitian mencakup analisis kebutuhan, desain sistem, implementasi algoritma, serta pengujian aplikasi melalui tahapan perhitungan MSE dan PSNR dari hasil enkripsi untuk mengukur tingkat kesalahan dan kualitas gambar hasil enkripsi. Hasil penelitian menunjukkan bahwa aplikasi ini berhasil mengenkripsi pesan serta menyembunyikannya dalam media gambar dengan baik. Aplikasi ini memberikan tingkat keamanan ganda dengan memadukan teknik kriptografi dan steganografi, sehingga pesan terlindungi dari pihak yang tidak berwenang. Penerapan algoritma Caesar Cipher menghasilkan pesan yang terenkripsi dan sulit diakses, sementara algoritma LSB mampu menyembunyikan pesan dalam gambar digital tanpa mempengaruhi kualitas visual. Penelitian ini membuktikan bahwa kombinasi kedua teknik ini efektif untuk menjaga kerahasiaan data.
Pengembangan Website Interaktif Untuk Memfasilitasi Minat Kebersihan Kelas di Kalangan Siswa Menengah Pertama Nugraha, Wildan Tisna Surya; Permana, Muhammad Fajar Jati; Sundari, Firda Rosela; Ikhsaniyah, Najwa; Abdurrahman, Hammam; Pradeka, Deden; Adiwilaga, Anugrah
JURNAL INFORMATIKA DAN KOMPUTER Vol 9, No 2 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v9i2.1340

Abstract

AbstrakPenelitian ini bertujuan untuk meningkatkan kualitas kebersihan kelas di lingkungan sekolah melalui implementasi website interaktif. Kebersihan kelas yang sering terabaikan memiliki dampak signifikan terhadap kesehatan dan konsentrasi siswa, sehingga mempengaruhi efektivitas pembelajaran. Oleh karena itu, penelitian ini mengembangkan sebuah website menggunakan model pengembangan interaktif Waterfall yang meliputi tahapan analisis kebutuhan, desan sistem, implementasi, danpengujian. Website ini dirancang untuk memudahkan penjadwalan piket, memberikan informasi kegiatan, dan memotivasau siswa melalui fitur Leaderboard. Implementasi menggunakan framework Laravel memastikan struktur yang kokoh dan fleksibel. Pengujian dengan metode Blackbox menunjukkan bahwa setiap fitur berfungsi dengan baik, meskipun perlu pengujian lebih lanjut dengan lebih banyak pengguna. Hasil penelitian ini diharapkan dapat memberikan solusi inovatif untuk mengatasi masalah kebersihan di sekolah, meningkatkan kesejahteraan siswa, dan mendukung proses pembelajaran yang lebih efektif.
Implementation of Least Significant Bit Steganography with Caesar Cipher Layout Dvorak web-based Kurnia, Ridhwan Nadif; Pradiptha, Al Diras; Permana, Muhammad Fajar Jati; Dipradja, Kimberly Alfa; Afrizal, Rizki; Pradeka, Deden; Khaerunnisa, Zahra
Jurnal Simantec Vol 14, No 1 (2025): Jurnal Simantec Desember 2025 (Article in Progress)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v14i1.28794

Abstract

Secure data communication is an essential requirement in the digital age, especially in the exchange of confidential information. One of the main problems is the potential for eavesdropping by unauthorised parties who can access open messages. To overcome this, this research aims to develop a website-based system that combines the Least Significant Bit (LSB) method steganography technique and the Caesar cipher method cryptography with the Dvorak keyboard layout to increase data security. The research method used is prototype method with the stages of concept formulation, prototype design, and continuous evaluation. The system was tested by inserting the word ‘TEKKOM’ into a digital image and measuring the quality using Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). The test results show an MSE value of 0.0001466049 and PSNR of 86.47 dB, which means that the visual quality of the image does not decrease significantly and the message is successfully inserted and extracted without errors. The Dvorak keyboard layout adds a layer of security through uncommon input patterns, making it difficult for outsiders to analyse. Thus, the system is able to provide a secure, efficient, and practical solution for web-based information hiding without the need for a database and is still user-friendly.Keywords: Dvorak, Steganography, Caesar Cipher, Least Significant Bit, Website
Comparative Study of the Effect of Datasets and Machine Learning Algorithms for PDF Malware Detection Wiharja, Salman; Pradeka, Deden; Suteddy, Wirmanto
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 1 (2024): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v15i1.19744

Abstract

This research presents an innovative approach to detecting malicious PDFs through machine learning algorithms, focusing on the expansion of the Evasive-PDFMal2022 dataset. The objective is to enhance the accuracy of detecting malicious PDFs by enriching the dataset, augmenting its representation and diversity, and developing a practical tool—a website—for extracting and detecting malicious PDFs. The methodology involves updating and enlarging the dataset with additional malicious PDFs sourced from CVE and Exploit-db, along with non-malicious PDFs from diverse origins. Features are then extracted using the PDFID tool, and these 20 features serve as the foundation for implementing K-Nearest Neighbor (KNN), Random Forest, and Random Committee algorithms. The outcomes demonstrate that the model trained with the expanded dataset achieves a remarkable 99% accuracy, surpassing the performance of models relying solely on the Evasive-PDFMal2022 dataset. Additionally, this research significantly enhances the representation and diversity of the dataset while delivering a practical solution in the form of a website tailored for the extraction and detection of malicious PDFs.
Pelatihan Robotika Sebagai Upaya Meningkatkan Kompetensi Keahlian Siswa SMK Daarut Tauhiid Bandung Muhammad Taufik Dwi Putra; Deden Pradeka; Anugrah Adiwilaga; Munawir Munawir; Dhimaz Purnama Adjhi
Jurnal Pengabdian UNDIKMA Vol. 4 No. 1 (2023): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v4i1.6516

Abstract

The rapid scientific development of robotics technology must be in line with efforts to increase the creativity and skills of human resources. Responding to these challenges, it is necessary to implement a robotics technology-based learning curriculum as early as possible starting from the school. However, there are some problems such as curriculum with robotics technology which is still rarely found in Indonesian schools. The purpose of this service is to improve the skills of students of SMK Daarut Tauhid through Robotics training. This method of devotion uses the method of lectures, hands-on practice, and interactive discussions. The number of participants in this training was 20 (twenty) students with activity evaluation instruments using g-form surveys and was analyzed descriptively. The results of this service show that student participants tend to better understand the scientific concepts of robotics technology when faced with real hardware compared to simulations using software. With this training, it’s hoped that knowledge and skills in robotics technology and science among students will increase.
Co-Authors Abdullah Muadz Nadzir Azhar Abdurrahman, Hammam Adi Suheryadi Adiwilaga, Anugrah Afrizal, Rizki Agus Juhana Ahdini, Allifia Alfarisi, Farhan Siddiq Ana Rahma Yuniarti Andhika R, Muhammad Auriel, Muhammad Deandy Zahran Vierdansyah Devi Aprianti Rimadhani Agustini Dhimaz Purnama Adjhi DIAN ANGGRAINI Dipradja, Kimberly Alfa Farisi, Farhan Siddiq Al Fauziah, Rahmah Fitriyani , Anisa Ghalbin Al Ghafiqi Graha Prakarsa Hendriyana Hendriyana Humaira, Syifa Aqila Ikhsaniyah, Najwa Jorgha Akram Aryandi Kartikasari, Ria Yuliani Khaerunnisa, Zahra Khoir, Farhan Ramadhan Kurnia, Ridhwan Nadif M. Ridwan Sutisna Manurung, Ferdinand Aprillian Maulana, Rajih Nibras Muhammad Azfa Faadhilah Muhammad Azmi Nugraha Muhammad Fahmi Pratama Muhammad Rizal Hanafi Munawir Munawir Munawir Munawir Nugraha, Wildan Tisna Surya Nuriman, Rizki Pararta, Muhammad Salam Permana, Muhammad Fajar Jati Pradana, Hilmil Pradiptha, Al Diras Putra, Muhammad Taufik Dwi Rizki Nuriman Sadik, Jafar Salman Abdul Jabbaar Wiharja Saragi, Muhammad Salam Pararta Septiana, Asyifa Imanda Suheryadi, Adi Sundari, Firda Rosela Syifaul Fuada Wiharja, Salman Wirmanto Suteddy Yahya Aliman Aidil Basith Zuhairmawan, Muhammad Tiar